디지털금융 시대의 제조식품 가격 예측 모델 개발: AI 기반 원재료 가격 예측을 통한 지능형 가격 의사결정시스템 연구

In a situation where consumer dissatisfaction is increasing due to companies raising prices despite the current price stability, the need to introduce an intelligent price decision system using artificial intelligence (AI) is growing. When such a system is introduced, it can be used as a key indicator against rising raw material prices from a company's point of view and as a trust-based marketing tool for consumers. In addition, from a financial investment perspective, it can be an important criterion for determining investment in raw material futures and food manufacturing companies. In order to overcome the limitations of current price prediction models using artificial intelligence, especially the problem of lowering prediction accuracy in case of macroeconomic shock, this study attempted to explore the possibility of implementing an intelligent price decision system for manufactured food using AI models. To this end, a price prediction model was constructed using various AI models such as ARIMAX, VAR, LSTM, and GRU, and the LSTM model showed the best performance after differentiation. Finally, the system proposed ‘price increase’ among ‘price increase’, ‘price freeze (gradual increase/fall)’, and ‘price decline’. Academically, this study implemented a manufactured food price prediction model using AI and suggested a new research direction for processed food price prediction, suggesting that it can be used as a standard for efficient raw material supply management by companies and key investment judgment by financial investors.